Medical Image Classification

Medical Image Classification is a task in medical image analysis that involves classifying medical images, such as X-rays, MRI scans, and CT scans, into different categories based on the type of image or the presence of specific structures or diseases. The goal is to use computer algorithms to automatically identify and classify medical images based on their content, which can help in diagnosis, treatment planning, and disease monitoring.

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 91–100 of 424 papers

Title	Date	Tasks	Status	Hype
Semi-supervised Medical Image Classification with Relation-driven Self-ensembling Model	May 15, 2020	ClassificationGeneral Classification	CodeCode Available	1
Tensor Networks for Medical Image Classification	Apr 21, 2020	BIG-bench Machine LearningClassification	CodeCode Available	1
Res2Net: A New Multi-scale Backbone Architecture	Apr 2, 2019	Image ClassificationInstance Segmentation	CodeCode Available	1
Evolutionary Neural AutoML for Deep Learning	Feb 18, 2019	AutoMLDeep Learning	CodeCode Available	1
Semi-Supervised Deep Learning for Abnormality Classification in Retinal Images	Dec 19, 2018	Deep LearningGeneral Classification	CodeCode Available	1
Densely Connected Convolutional Networks	Aug 25, 2016	Breast Tumour ClassificationClassification	CodeCode Available	1
FedGSCA: Medical Federated Learning with Global Sample Selector and Client Adaptive Adjuster under Label Noise	Jul 13, 2025	Federated Learningimage-classification	—Unverified	0
Robust Training with Data Augmentation for Medical Imaging Classification	Jun 20, 2025	Data AugmentationDiagnostic	—Unverified	0
Finding Optimal Kernel Size and Dimension in Convolutional Neural Networks An Architecture Optimization Approach	Jun 16, 2025	Computational Efficiencyimage-classification	—Unverified	0
Detecção da Psoríase Utilizando Visão Computacional: Uma Abordagem Comparativa Entre CNNs e Vision Transformers	Jun 11, 2025	image-classificationImage Classification	—Unverified	0

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All datasets NCT-CRC-HE-100K IDRiD ImageNet PCOS Classification CheXphoto Galaxy10 DECals ISIC 2017 ISIC 2020 Challenge Dataset Malaria Dataset OASIS 3

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	Efficientnet-b0	Accuracy (%)	95.59	—	Unverified
2	ResNeXt-50-32x4d	Accuracy (%)	95.46	—	Unverified
3	RegNetY-3.2GF	Accuracy (%)	95.42	—	Unverified
4	ResNet-50	Accuracy (%)	94.72	—	Unverified
5	DenseNet-169	Accuracy (%)	94.41	—	Unverified
6	Res2Net-50	Accuracy (%)	93.37	—	Unverified
7	ResNet-18	Accuracy (%)	92.66	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ResNet-152	Accuracy (% )	86.56	—	Unverified
2	Beta-Rank	Accuracy	81.88	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DaViT-S	GFLOPs	8.8	—	Unverified
2	DaViT-T	GFLOPs	4.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	InceptionV3	1:1 Accuracy	90.2	—	Unverified
2	EfficientNet B7	1:1 Accuracy	88.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	PTRN	Mean AUC	0.85	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Astroformer	Top-1 Accuracy (%)	94.87	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Beta-Rank	Accuracy	72.44	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	EfficientNet Ensemble	AUC	0.95	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SNAPSHOT ENSEMBLE	F1 score	99.37	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	3D CNN	AUC	87	—	Unverified